Corrigendum to "Long-term cardiovascular outcomes in COVID-19 survivors among non-vaccinated population: a retrospective cohort study from the TriNetX US collaborative networks".

[This corrects the article DOI: 10.1016/j.eclinm.2022.101619.].

Ferrets: A powerful model of SARS-CoV-2.

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in recent years not only caused a global pandemic but resulted in enormous social, economic, and health burdens worldwide. Despite considerable efforts to combat coronavirus disease 2019 (COVID-19), various SARS-CoV-2 variants have emerged, and their underlying mechanisms of pathogenicity remain largely unknown. Furthermore, effective therapeutic drugs are still under development. Thus, an ideal animal model is crucial for studying the pathogenesis of COVID-19 and for the preclinical evaluation of vaccines and antivirals against SARS-CoV-2 and variant infections. Currently, several animal models, including mice, hamsters, ferrets, and non-human primates (NHPs), have been established to study COVID-19. Among them, ferrets are naturally susceptible to SARS-CoV-2 infection and are considered suitable for COVID-19 study. Here, we summarize recent developments and application of SARS-CoV-2 ferret models in studies on pathogenesis, therapeutic agents, and vaccines, and provide a perspective on the role of these models in preventing COVID-19 spread.

Efficacy and safety of granulocyte-macrophage colony-stimulating factor (GM-CSF) antibodies in COVID-19 patients: a meta-analysis.

OBJECTIVE: This study aims to determine the efficacy and safety of granulocyte-macrophage colony-stimulating factor (GM-CSF) antibodies in COVID-19 patients. METHODS: We searched Cochrane Library, PubMed, Embase, and ClinicalTrials.gov databases until July 27, 2022. Both randomized control trials (RCTs) and cohort studies were included and analyzed separately. The outcomes included mortality, incidence of invasive mechanical ventilation (IMV), ventilation improvement rate (need oxygen therapy to without oxygen therapy), secondary infection, and adverse events (AEs). The odds ratio (OR) with a 95% confidence interval (CI) was calculated by a random-effects meta-analysis model. RESULTS: Five RCTs and 2 cohort studies with 1726 COVID-19 patients were recruited (n = 866 in the GM-CSF antibody group and n = 891 in the control group). GM-CSF antibodies treatment reduced the incidence of IMV, which was supported by two cohort studies (OR 0.16; 95% CI 0.03, 0.74) and three RCTs (OR 0.62; 95% CI 0.41, 0.94). GM-CSF antibodies resulted in slight but not significant reductions in mortality (based on two cohort studies and five RCTs) and ventilation improvement (based on one cohort study and two RCTs). The sensitive analysis further showed the results of mortality and ventilation improvement rate became statistically significant when one included study was removed. Besides, GM-CSF antibodies did not increase the risks of the second infection (based on one cohort study and five RCTs) and AEs (based on five RCTs). CONCLUSION: GM-CSF antibody treatments may be an efficacious and well-tolerant way for the treatment of COVID-19. Further clinical evidence is still warranted.

Lyophilized mRNA-lipid nanoparticle vaccines with long-term stability and high antigenicity against SARS-CoV-2.

Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, most current mRNA delivery platforms need to be stored at -20 °C or -70 °C due to their poor stability, which severely restricts their availability. Herein, we develop a lyophilization technique to prepare SARS-CoV-2 mRNA-lipid nanoparticle vaccines with long-term thermostability. The physiochemical properties and bioactivities of lyophilized vaccines showed no change at 25 °C over 6 months, and the lyophilized SARS-CoV-2 mRNA vaccines could elicit potent humoral and cellular immunity whether in mice, rabbits, or rhesus macaques. Furthermore, in the human trial, administration of lyophilized Omicron mRNA vaccine as a booster shot also engendered strong immunity without severe adverse events, where the titers of neutralizing antibodies against Omicron BA.1/BA.2/BA.4 were increased by at least 253-fold after a booster shot following two doses of the commercial inactivated vaccine, CoronaVac. This lyophilization platform overcomes the instability of mRNA vaccines without affecting their bioactivity and significantly improves their accessibility, particularly in remote regions.

Efficacy and safety of granulocyte–macrophage colony-stimulating factor (GM-CSF) antibodies in COVID-19 patients: a meta-analysis

Objective This study aims to determine the efficacy and safety of granulocyte–macrophage colony-stimulating factor (GM-CSF) antibodies in COVID-19 patients. Methods We searched Cochrane Library, PubMed, Embase, and ClinicalTrials.gov databases until July 27, 2022. Both randomized control trials (RCTs) and cohort studies were included and analyzed separately. The outcomes included mortality, incidence of invasive mechanical ventilation (IMV), ventilation improvement rate (need oxygen therapy to without oxygen therapy), secondary infection, and adverse events (AEs). The odds ratio (OR) with a 95% confidence interval (CI) was calculated by a random-effects meta-analysis model. Results Five RCTs and 2 cohort studies with 1726 COVID-19 patients were recruited (n = 866 in the GM-CSF antibody group and n = 891 in the control group). GM-CSF antibodies treatment reduced the incidence of IMV, which was supported by two cohort studies (OR 0.16;95% CI 0.03, 0.74) and three RCTs (OR 0.62;95% CI 0.41, 0.94). GM-CSF antibodies resulted in slight but not significant reductions in mortality (based on two cohort studies and five RCTs) and ventilation improvement (based on one cohort study and two RCTs). The sensitive analysis further showed the results of mortality and ventilation improvement rate became statistically significant when one included study was removed. Besides, GM-CSF antibodies did not increase the risks of the second infection (based on one cohort study and five RCTs) and AEs (based on five RCTs). Conclusion GM-CSF antibody treatments may be an efficacious and well-tolerant way for the treatment of COVID-19. Further clinical evidence is still warranted. Supplementary Information The online version contains supplementary material available at 10.1007/s10787-022-01105-9.

Decoy Nanozymes Enable Multitarget Blockade of Proinflammatory Cascades for the Treatment of Multi-Drug-Resistant Bacterial Sepsis.

Sepsis is a life-threatening organ dysfunction characterized by severe systemic inflammatory response to infection. Effective treatment of bacterial sepsis remains a paramount clinical challenge, due to its astonishingly rapid progression and the prevalence of bacterial drug resistance. Here, we present a decoy nanozyme-enabled intervention strategy for multitarget blockade of proinflammatory cascades to treat multi-drug-resistant (MDR) bacterial sepsis. The decoy nanozymes (named MCeC@MΦ) consist mesoporous silica nanoparticle cores loaded with CeO2 nanocatalyst and Ce6 photosensitizer and biomimetic shells of macrophage membrane. By acting as macrophage decoys, MCeC@MΦ allow targeted photodynamic eradication of MDR bacteria and realize simultaneous endotoxin/proinflammatory cytokine neutralization. Meanwhile, MCeC@MΦ possess intriguing superoxide dismutase and catalase-like activities as well as hydroxyl radical antioxidant capacity and enable catalytic scavenging of multiple reactive oxygen species (ROS). These unique capabilities make MCeC@MΦ to collaboratively address the issues of bacterial infection, endotoxin/proinflammatory cytokine secretion, and ROS burst, fully cutting off the path of proinflammatory cascades to reverse the progression of bacterial sepsis. In vivo experiments demonstrate that MCeC@MΦ considerably attenuate systemic hyperinflammation and rapidly rescue organ damage within 1 day to confer higher survival rates (>75%) to mice with progressive MDR Escherichia coli bacteremia. The proposed decoy nanozyme-enabled multitarget collaborative intervention strategy offers a powerful modality for bacterial sepsis management and opens up possibilities for the treatment of cytokine storm in the COVID-19 pandemic and immune-mediated inflammation diseases.

Long-term cardiovascular outcomes in COVID-19 survivors among non-vaccinated population: A retrospective cohort study from the TriNetX US collaborative networks.

Background: The long-term cardiovascular outcomes in COVID-19 survivors remain largely unclear. The aim of this study was to investigate the long-term cardiovascular outcomes in COVID-19 survivors. Methods: This study used the data from the US Collaborative Network in TriNetX. From a cohort of more than 42 million records between 1 January 2019 and 31 March 2022, a total of 4,131,717 participants who underwent SARS-CoV-2 testing were recruited. Study population then divided into two groups based on COVID-19 test results. To avoid reverse causality, the follow-up initiated 30 days after the test, and continued until 12 months. Hazard ratios (HRs) and 95% Confidence intervals (CIs) of the incidental cardiovascular outcomes were calculated between propensity score-matched patients with versus without SARS-CoV-2 infection. Subgroup analyses on sex, and age group were also conducted. Sensitivity analyses were performed using different network, or stratified by hospitalization to explore the difference of geography and severity of COVID-19 infection. Findings: The COVID-19 survivors were associated with increased risks of cerebrovascular diseases, such as stroke (HR [95% CI] = 1.618 [1.545-1.694]), arrhythmia related disorders, such as atrial fibrillation (HR [95% CI] = 2.407 [2.296-2.523]), inflammatory heart disease, such as myocarditis (HR [95% CI] =4.406 [2.890-6.716]), ischemic heart disease(IHD), like ischemic cardiomyopathy (HR [95% CI] = 2.811 [2.477-3.190]), other cardiac disorders, such as heart failure (HR [95% CI] =2.296 [2.200-2.396]) and thromboembolic disorders (e.g. pulmonary embolism: HR [95% CI] =2.648 [2.443-2.870]). The risks of two composite endpoints, major adverse cardiovascular event (HR [95% CI] = 1.871 [1.816-1.927]) and any cardiovascular outcome (HR [95% CI] = 1.552 [1.526-1.578]), were also higher in the COVID-19 survivors than in the controls. Moreover, the survival probability of the COVID-19 survivors dramatically decreased in all the cardiovascular outcomes. The risks of cardiovascular outcomes were evident in both male and female COVID-19 survivors. Furthermore, the risk of mortality was higher in the elderly COVID-19 survivors (age ≥ 65 years) than in the young ones. Sensitivity analyses presented roughly similar results globally. Furthermore, the impact of COVID-19 on cardio-related outcomes appeared to be more pronounced in inpatients than in outpatients. Interpretation: The 12-month risk of incidental cardiovascular diseases is substantially higher in the COVID-19 survivors than the non-COVID-19 controls. Clinicians and patients with a history of COVID-19 should pay attention to their cardiovascular health in long term. Funding: The Fundamental Research Funds for the Central public welfare research institutes and Young Elite Scientists Sponsorship Program by CACM.

Application of Visitor Eye Movement Information to Museum Exhibit Analysis

The motivation of this study is that after the COVID-19 epidemic, museum exhibition visits have also been significantly affected. The purpose of this research is to better understand the visual cognition of visitors, so as to improve the application of physical field or online exhibitions. Currently, no research is available on the differences in the visitor's viewing and cognitive process with eye movements sequence analysis that stem from the exhibition planning and design of different museums. This study tracks and analyzes the eye movement trajectories of visitors and studies its relation to learning and cognition and finds the key to influencing cognition through behavioral sequence analysis of displayed content. The results show that those interested in the displayed content have better cognitive performance, are immersed in reading text, and have a substantial shift in eye movement. Contrarily, those not interested in the displayed content are distracted and often turn their attention back to the title of the content. In this study, eye movement and fixation are indicators that can be used as a reference for the future design of displays to improve the effectiveness of presenting information to a visitor. Furthermore, this research can also provide future applications in integrating the virtual world and cognitive information, in the application of AR, VR, or metaverse environment, to provide people's cognition of rapid information in the virtual environment.

A meta-analysis of granulocyte-macrophage colony-stimulating factor (GM-CSF) antibody treatment for COVID-19 patients.

OBJECTIVE: This meta-analysis aims to assess the efficacy and safety of granulocyte-macrophage colony-stimulating factor (GM-CSF) antibodies on COVID-19. METHODS: Relevant literatures about GM-CSF antibody treatment in COVID-19 patients were searched from the PubMed, Cochrane Library, Embase, Google scholar, and Baiduscholar databases from the COVID-19 outbreak in December 2019 until 1 January 2021. The primary outcomes included the death, intensive care unit (ICU) admission risk, ventilation requirement, and secondary infection. RESULTS: A total of 12 eligible literature involving 8979 COVID-19 patients were recruited, and they were divided into experimental group (n = 2673) and control group (n = 6306). Using a random-effect model, it is found that the GM-CSF antibody treatment was associated with a 23% decline of the risk of death [odd's ratio (OR): 0.34, 95% confidence interval (CI): 0.21-0.56, p < 0.0001] and a 20% enhancement of ventilation (OR: 1.47, 95% CI: 1.19, 1.80, p = 0.0002). GM-CSF antibody treatment did not have a significant correlation to secondary infection and increased risk of ICU admission in COVID-19 patients, which may be attributed to the older age and the length of stay. CONCLUSIONS: Severe COVID-19 patients can benefit from GM-CSF antibodies.

A novel framework integrating AI model and enzymological experiments promotes identification of SARS-CoV-2 3CL protease inhibitors and activity-based probe.

The identification of protein-ligand interaction plays a key role in biochemical research and drug discovery. Although deep learning has recently shown great promise in discovering new drugs, there remains a gap between deep learning-based and experimental approaches. Here, we propose a novel framework, named AIMEE, integrating AI model and enzymological experiments, to identify inhibitors against 3CL protease of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), which has taken a significant toll on people across the globe. From a bioactive chemical library, we have conducted two rounds of experiments and identified six novel inhibitors with a hit rate of 29.41%, and four of them showed an IC50 value <3 µM. Moreover, we explored the interpretability of the central model in AIMEE, mapping the deep learning extracted features to the domain knowledge of chemical properties. Based on this knowledge, a commercially available compound was selected and was proven to be an activity-based probe of 3CLpro. This work highlights the great potential of combining deep learning models and biochemical experiments for intelligent iteration and for expanding the boundaries of drug discovery. The code and data are available at https://github.com/SIAT-code/AIMEE.

Risk factors and prediction nomogram model for psychosocial and behavioural problems among children and adolescents during the COVID-19 pandemic: A national multicentre study: Risk Factors of Childhood Psychosocial Problems.

BACKGROUND: We aimed to explore the risk profiles attributable to psychosocial and behavioural problems during the coronavirus disease 2019 pandemic. To this end, we created a risk-prediction nomogram model. METHODS: A national multicentre study was conducted through an online questionnaire involving 12,186 children (6-11 years old) and adolescents (12-16 years old). Respondents' psychosocial and behavioural functioning were assessed using the Achenbach Child Behaviour Checklist (CBCL). Data were analysed using STATA software and R-language. RESULTS: The positive detection rate of psychological problems within Wuhan was greater than that outside Wuhan for schizoid (P = 0.005), and depression (P = 0.030) in children, and for somatic complaints (P = 0.048), immaturity (P = 0.023), and delinquent behaviour (P = 0.046) in adolescents. After graded multivariable adjustment, seven factors associated with psychological problems in children and adolescents outside Wuhan were parent-child conflict (odds ratio (OR): 4.94, 95% confidence interval (95% CI): 4.27-5.72), sleep problems (OR: 4.05, 95% CI: 3.77-4.36), online study time (OR: 0.41, 95% CI: 0.37-0.47), physical activity time (OR: 0.510, 95% CI: 0.44-0.59), number of close friends (OR: 0.51, 95% CI: 0.44-0.6), time spent playing videogames (OR: 2.26, 95% CI: 1.90-2.69) and eating disorders (OR: 2.71, 95% CI: 2.35-3.11) (all P < 0.001). Contrastingly, within Wuhan, only the first four factors, namely, parent-child conflict (5.95, 2.82-12.57), sleep problems (4.47, 3.06-6.54), online study time (0.37, 0.22-0.64), and physical activity time (0.42, 0.22-0.80) were identified (all P < 0.01). Accordingly, nomogram models were created with significant attributes and had decent prediction performance with C-indexes over 80%. LIMITATION: A cross-sectional study and self-reported measures. CONCLUSIONS: Besides the four significant risk factors within and outside Wuhan, the three additional factors outside Wuhan deserve special attention. The prediction nomogram models constructed in this study have important clinical and public health implications for psychosocial and behavioural assessment.

Psychosocial and behavioral problems of children and adolescents in the early stage of reopening schools after the COVID-19 pandemic: a national cross-sectional study in China.

This study aims to explore the psychosocial and behavioral problems of children and adolescents in the early stage of reopening schools. In this national cross-sectional study, a total of 11072 students from China were naturally divided into two groups based on their schooling status: reopened schools (RS) and home schooling (HS) group. The psychosocial and behavioral functioning were measured by Achenbach Child Behaviour Checklist (CBCL) and compared in these two groups. Multivariable logistic regression analyses were conducted to explore the independent predictors associated with the psychosocial and behavioral problems. Our results showed that the students in the RS group had more adverse behaviors than that of HS group. The RS group had the higher rates of parent-offspring conflict, prolonged homework time, increased sedentary time and sleep problems (all p < 0.001). When separate analyses were conducted in boys and girls, the RS group had the higher scores for (1) overall behavioral problems (p = 0.02 and p = 0.01), internalizing (p = 0.02 and p = 0.02) and externalizing (p = 0.02 and p = 0.004) behaviors in the 6-11 age group; (2) externalizing (p = 0.049 and p = 0.006) behaviors in the 12-16 age group. Multivariable regression showed parent-offspring conflict and increased sedentary time were the most common risk factors, while physical activity and number of close friends were protective factors for behavior problems in RS students (p < 0.01 or 0.05). The present study revealed that students' psychosocial and behavioral problems increased in the early stage of schools reopened unexpectedly. These findings suggest that close attention must be paid and holistic strategies employed in the school reopening process of post-COVID-19 period.

Understanding the Complex Adoption Behavior of Cloud Services by SMEs Based on Complexity Theory: A Fuzzy Sets Qualitative Comparative Analysis (fsQCA)

To survive in a competitive environment, small and medium enterprises (SMEs) have had to adapt to the digital environment in order to adjust to customer needs globally, particularly in the post-COVID-19 world. The advantages of cloud computing (e.g., flexibility, scalability, and low entry cost) provide opportunities for SMEs with a restricted budget and limited resources. To understand how SMEs adopt cloud computing in a complex digital environment, this study examines how antecedents combine with each other to explain the high adoption of cloud computing. From the perspectives of holism and set theory, we draw on complexity and configuration theories, present a conceptual model including seven antecedents based on the technology-organization-environment framework, and conduct an asymmetric fuzzy-set qualitative comparative analysis. Through an empirical study with 123 Chinese companies, we identify nine combinations (configurations) of determinant antecedents that lead to the high adoption of cloud computing. The results show that none of the factors are indispensable to explain a high adoption on their own;instead, they are insufficient but necessary parts of the causal combinations that explain a high adoption. This study contributes to the literature on cloud computing adoption by extending current knowledge on how antecedents combine to increase the adoption and identify specific patterns of SMEs for whom these factors are essential and greatly influence their adoption.

Municipal utilities and COVID-19: Challenges, responses, and collaboration

The COVID-19 pandemic has put pressure on essential public services. While much of the economy has been shut down, essential public services have continued. Using professional experience, publicly available information, and interviews with two municipal utility managers, we evaluate the challenges presented to municipal utility services by the COVID-19 pandemic and explore some of the responses by utilities to the pandemic. Specifically, we focus on the strategies utilities have used to keep employees safe from the virus and plans for workforce shortages. One important strategy we identify is reliance on mutual aid agreements, where utilities agree to send staff and equipment to other utilities in times of crisis. We also explore the role of a municipal utility association in coordinating response. The case of utility response to COVID-19 carries important potential implications for both public administration practice and research. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

Municipal Utilities and COVID-19: Challenges, Responses, and Collaboration

The COVID-19 pandemic has put pressure on essential public services. While much of the economy has been shut down, essential public services have continued. Using professional experience, publicly available information, and interviews with two municipal utility managers, we evaluate the challenges presented to municipal utility services by the COVID-19 pandemic and explore some of the responses by utilities to the pandemic. Specifically, we focus on the strategies utilities have used to keep employees safe from the virus and plans for workforce shortages. One important strategy we identify is reliance on mutual aid agreements, where utilities agree to send staff and equipment to other utilities in times of crisis. We also explore the role of a municipal utility association in coordinating response. The case of utility response to COVID-19 carries important potential implications for both public administration practice and research.